Hi Andy,
Maybe it's just me, but the "left out data" threw me off. Perhaps, I would
integrate with your previous comments:
best_estimator_
estimator
Estimator that was chosen by the search, i.e. estimator which gave highest
average score (or smallest loss if specified) over the cross-validation folds.
on the left out data.
best_score_
float
Highest average score of the best_estimator computed above on the left out data.
Thank you,
From: Andy [mailto:[email protected]]
Sent: Friday, July 25, 2014 3:50 PM
To: [email protected]
Subject: Re: [Scikit-learn-general] gridSearchCV best_estimator_ best_score_
The best_score_ is the mean score of the best parameter averaged over folds.
best_estimator_ is the estimator with these parameters retrained on the whole
training set.
If this is not clear from the docstring, what alternative would you propose?
Best,
Andy
On 07/25/2014 09:32 PM, Pagliari, Roberto wrote:
I'm not sure if I understand the documentation of gridSearchCV:
best_estimator_
estimator
Estimator that was chosen by the search, i.e. estimator which gave highest
score (or smallest loss if specified) on the left out data.
best_score_
float
Score of best_estimator on the left out data.
Shouldn't they be the best estimator and best score averaged over the k
partition (when using kfold for cross validation)?
If not, is there a way to set this constraint?
Thank you,
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